agent-bom

# agent-bom — AI Agent Infrastructure Security Scanner

Discovers MCP clients and servers across 22 AI tools, scans for CVEs, maps blast radius, runs cloud CIS benchmarks, checks OWASP/NIST/MITRE compliance, generates SBOMs, and assesses AI infrastructure against AISVS v1.0 and MAESTRO framework layers.

Install

```bash pipx install agent-bom agent-bom scan # auto-discover + scan agent-bom check langchain # check a specific package agent-bom fs . # scan filesystem packages agent-bom image nginx:1.25 # scan container image (native, no Syft) agent-bom cloud aws # AWS CIS benchmark agent-bom iac infra/ # scan Terraform/CloudFormation agent-bom where # show all discovery paths ```

As an MCP Server

```json { "mcpServers": { "agent-bom": { "command": "uvx", "args": ["agent-bom", "mcp"] } } } ```

Tools (32)

Vulnerability Scanning | Tool | Description | |------|-------------| | `scan` | Full discovery + vulnerability scan pipeline | | `check` | Check a package for CVEs (OSV, NVD, EPSS, KEV) | | `blast_radius` | Map CVE impact chain across agents, servers, credentials | | `remediate` | Prioritized remediation plan for vulnerabilities | | `verify` | Package integrity + SLSA provenance check | | `diff` | Compare two scan reports (new/resolved/persistent) | | `where` | Show MCP client config discovery paths | | `inventory` | List discovered agents, servers, packages |

Compliance & Policy | Tool | Description | |------|-------------| | `compliance` | OWASP LLM/Agentic Top 10, EU AI Act, MITRE ATLAS, NIST AI RMF | | `policy_check` | Evaluate results against custom security policy (17 conditions) | | `cis_benchmark` | CIS benchmark checks (AWS, Azure v3.0, GCP v3.0, Snowflake) | | `generate_sbom` | Generate SBOM (CycloneDX or SPDX format) | | `aisvs_benchmark` | OWASP AISVS v1.0 compliance — 9 AI security checks |

Registry & Trust | Tool | Description | |------|-------------| | `registry_lookup` | Look up MCP server in 427+ server security metadata registry | | `marketplace_check` | Pre-install trust check with registry cross-reference | | `fleet_scan` | Batch registry lookup + risk scoring for MCP server inventories | | `skill_trust` | Assess skill file trust level (5-category analysis) | | `code_scan` | SAST scanning via Semgrep with CWE-based compliance mapping |

Runtime & Analytics | Tool | Description | |------|-------------| | `context_graph` | Agent context graph with lateral movement analysis | | `analytics_query` | Query vulnerability trends, posture history, and runtime events | | `runtime_correlate` | Cross-reference proxy audit JSONL with CVE findings, risk amplification | | `vector_db_scan` | Probe Qdrant/Weaviate/Chroma/Milvus for auth and exposure | | `gpu_infra_scan` | GPU container and K8s node inventory + unauthenticated DCGM probe (MAESTRO KC6) |

Specialized Scans | Tool | Description | |------|-------------| | `dataset_card_scan` | Scan dataset cards for bias, licensing, and provenance issues | | `training_pipeline_scan` | Scan training pipeline configs for security risks | | `browser_extension_scan` | Scan browser extensions for risky permissions and AI domain access | | `model_provenance_scan` | Verify model provenance and supply chain integrity | | `prompt_scan` | Scan prompt templates for injection and data leakage risks | | `model_file_scan` | Scan model files for unsafe serialization (pickle, etc.) | | `license_compliance_scan` | Full SPDX license catalog scan with copyleft and network-copyleft detection | | `ingest_external_scan` | Import Trivy/Grype/Syft scan results and merge into agent-bom findings |

Resources | Resource | Description | |----------|-------------| | `registry://servers` | Browse 427+ MCP server security metadata registry |

Example Workflows

``` # Check a package before installing check(package="@modelcontextprotocol/server-filesystem", ecosystem="npm")

# Map blast radius of a CVE blast_radius(cve_id="CVE-2024-21538")

# Full scan scan()

# Run CIS benchmark cis_benchmark(provider="aws")

# Run AISVS v1.0 compliance aisvs_benchmark()

# Scan vector databases for auth misconfigurations vector_db_scan()

# Discover GPU containers, K8s GPU nodes, and unauthenticated DCGM endpoints gpu_infra_scan()

# Assess trust of a skill file skill_trust(skill_content="<paste SKILL.md content>") ```

Guardrails

• Always do:
• Show CVEs even when NVD analysis is pending or severity is `unknown` — a CVE ID with no details is still a real finding. Report what is known; mark severity as `unknown` explicitly.
• Confirm with the user before scanning cloud environments (`cis_benchmark`) — these make live API calls to AWS/Azure/GCP using the user's credentials.
• Treat `UNKNOWN` severity as unresolved, not benign — it means data is not yet available, not that the issue is minor.

• Never do:
• Do not modify any files, install packages, or change system configuration. This skill is read-only.
• Do not transmit env var values, credentials, or file contents to any external service. Only package names and CVE IDs leave the machine.
• Do not invoke `scan()` autonomously on sensitive environments without user confirmation. The `autonomous_invocation` policy is `restricted`.

• Stop and ask the user when:
• The user requests a cloud CIS benchmark and no cloud credentials are configured.
• A scan finds `CRITICAL` CVEs — present findings and ask whether to generate a remediation plan.
• The user asks to scan a path outside their home directory.

Supported Frameworks (14)

• OWASP LLM Top 10 (2025) — prompt injection, supply chain, data leakage
• OWASP MCP Top 10 — MCP-specific security risks
• OWASP Agentic Top 10 — tool poisoning, rug pulls, credential theft
• OWASP AISVS v1.0 — AI Security Verification Standard (9 checks)
• MITRE ATLAS — adversarial ML threat framework
• NIST AI RMF — govern, map, measure, manage lifecycle
• NIST CSF 2.0 — identify, protect, detect, respond, recover
• NIST 800-53 Rev 5 — federal security controls (CM-8, RA-5, SI-2, SR-3)
• FedRAMP Moderate — derived from NIST 800-53 controls
• EU AI Act — risk classification, transparency, SBOM requirements
• ISO 27001:2022 — information security controls (Annex A)
• SOC 2 — Trust Services Criteria
• CIS Controls v8 — implementation groups IG1/IG2/IG3
• CMMC 2.0 — cybersecurity maturity model (Level 1-3)

Privacy & Data Handling

This skill installs agent-bom from PyPI. **Verify the redaction behavior before running with any config files:**

```bash # Step 1: Install pip install agent-bom

# Step 2: Review redaction logic BEFORE scanning # sanitize_env_vars() replaces ALL env var values with *REDACTED* # BEFORE any config data is processed or stored: # https://github.com/msaad00/agent-bom/blob/main/src/agent_bom/security.py#L159

# Step 3: Review config parsing — only structural data extracted: # https://github.com/msaad00/agent-bom/blob/main/src/agent_bom/discovery/__init__.py

# Step 4: Verify package provenance (Sigstore) agent-bom verify agent-bom

# Step 5: Only then run scans agent-bom scan ```

What is extracted: Server names, commands, args, and URLs from MCP client config files across 22 AI tools. What is NOT extracted: Env var values are replaced with `*REDACTED*` by `sanitize_env_vars()` before any processing. Only public package names and CVE IDs are sent to vulnerability databases. Cloud CIS checks use locally configured credentials and call only the cloud provider's own APIs.

Verification

• Source: github.com/msaad00/agent-bom (Apache-2.0)
• Sigstore signed: `agent-bom verify [email protected]`
• 6,533+ tests with CodeQL + OpenSSF Scorecard
• No telemetry: Zero tracking, zero analytics